Attractivity or Repellence: Relation between the Endophytic Fungi of <i>Acalypha</i>, <i>Colocasia</i>and the Leaf-Cutting Ants—<i>Atta sexdens</i>

Symbiotic relations are present in the nature and can contribute to the success of the organisms involved. Endophytic fungi live within the leaf tissues without causing any harm to the host plant, and some of them can be a defense mechanism against the attack by the leaf-cutting ants. Ants of the genus Atta are known as leaf-cutting ants and have an obligatory association with the fungus Leucoagaricus gongylophorus, cutting pieces of leaves and bringing them back to the colony to the fungus. The present study aimed to find out the endophytic fungi community of an attractive plant (Acalypha wilkesiana) and a less attractive plant (Colocasia esculenta) to the ants Atta sexdens. We found out that the communities are different in quantity and in composition and 73% of the isolated fungi were from A. wilkesiana, which has fungi known as attractive to leaf-cutting ants, such as genus Colletotrichum, Pestalotiopsis, Phomopsis and Xylaria. On the other hand, in C. esculenta, there was found the genus Fusarium, known to be reject by the leaf-cutting ants, and less fungal diversity than in the attractive plant A. wilkesiana. Therefore, our data suggest that attractivity or repelence of a plant to the leaf-cutting ants could be related to presence or ausence of determinated fungi more than the quantity of fungi present in a leaf.

Acromyrmex ameliae sp. n. （Hymenoptera： Formicidae）： A new social parasite of leaf-cutting ants in Brazil

The fungus-growing ants （Tribe Attini） are a New World group of〉 200 species, all obligate symbionts with a fungus they use for food. Four attine taxa are known to be social parasites of other attines. Acromyrmex （ Pseudoatta） argentina argentina and Acromyrmex （Pseudoatta） argentina platensis （parasites of Acromyrmex lundi）, and Acromyrmex sp. （a parasite of Acromyrmex rugosus） produce no worker caste. In contrast, the recently discovered Acromyrmex insinuator （a parasite of Acromyrmex echinatior） does produce workers. Here, we describe a new species, Acromyrmex ameliae, a social parasite of Acromyrmex subterraneus subterraneus and Acromyrmex subterraneus brunneus in Minas Gerais, Brasil. Like A. insinuator, it produces workers and appears to be closely related to its hosts. Similar social parasites may be fairly common in the fungus-growing ants, but overlooked due to the close resemblance between parasite and host workers.

Micro-Arthropods in the Surroundings of Nests of Messor arenarius Ants in the Negev Desert in Israel

The present research investigated a segment of the micro-arthropod populations residing within nests of Messor arenarius ants in the Negev Desert of Israel. The total frequencies of micro-arthropods in the chaff of those ants’ nests were found to be higher than in the surrounding soil of the same nests. Acari (mites) were observed to be more abundant during the spring season, whereas their presence decreased during the summer months. Springtails (Collembola) were found to follow the Acari pattern, commonly found within the nests of those ants during spring but were absent during summer. Psocoptera order inhabiting soil habitats were infrequently encountered during spring, but their prevalence increased significantly during summer, particularly within the chaff of the ants’ nests, suggesting that chaff is their primary food source in the Negev Desert. Our research suggests that shifts in seasonality have important consequences on the distribution of soil invertebrate communities with implications on nutrient cycling.

Novel Phialophora species from leaf-cutting ants (tribe Attini)

Ants in the tribe Attini(Hymenoptera,Formicidae)maintain a 50 million-year-old lifestyle of co-evolution with symbiotic basidiomycetous fungi which they cultivate as essential source of nutrition.However,other microorganisms have been reported from ant habitats indicating a higher diversity of consistently associated species than established to date.Recently,black yeast-like fungi have been reported as a possible symbiont,like a competitor of the actinomycete bacteria that grow in the integument of the insects.During the mating season,gynes of Atta capiguara and A.laevigata were collected from nests located in Botucatu,SP,Brazil and sampled using flotation technique.Phylogenetic analysis based on ITS,partial 28S(LSU)andβ-tubulin sequences revealed the occurrence of two novel species of Phialophora among the melanized fungi isolated.

Optical redox imaging of ANT1-de-cient muscles

Adenine nucleotide translocator(ANT)is a mitochondrial protein involved in the exchange of ADP and ATP across the mitochondrial inner membrane.It plays a crucial role in cellular energy metabolism by facilitating the transport of ATP synthesized within the mitochondria to the cytoplasm.The isoform ANT1 predominately expresses in cardiac and skeletal muscles.Mutations or dysregulation in ANT1 have been implicated in various mitochondrial disorders and neuromuscular diseases.We aimed to examine whether ANT1 deletion may affect mitochondrial redox state in our established ANT1-de-cient mice.Hearts and quadriceps resected from age-matched wild type(WT)and ANT1-de-cient mice were snap-frozen in liquid nitrogen.The Chance redox scanner was utilized to perform 3D optical redox imaging.Each sample underwent scanning across 3–5 sections.Global averaging analysis showed no signi-cant differences in the redox indices(NADH,flavin adenine dinucleotide containing-flavoproteins Fp,and the redox ratio Fp/(NADH+Fp)between WT and ANT1-de-cient groups.However,quadriceps had higher Fp than hearts in both groups(p¼0:0004 and 0.01,respectively).Furthermore,the quadriceps were also more oxidized(a higher redox ratio)than hearts in WT group(p¼0:004).NADH levels were similar in all cases.Our data suggest that under non-stressful physical condition,the ANT1-de-cient muscle cells were in the same mitochondrial state as WT ones and that the signi-cant difference in the mitochondrial redox state between quadriceps and hearts found in WT might be diminished in ANT1-de-cient ones.Redox imaging of muscles under physical stress can be conducted in future.

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

基于Ant Design Pro的物流系统前端开发与用户体验优化研究

本文探讨了Ant Design Pro在物流系统开发中的应用,特别是其对用户体验和数据可视化的影响。通过采用案例研究方法,分析Ant Design Pro在构建企业级物流系统中的应用。研究发现,Ant Design Pro的一致性设计和丰富的组件库显著提升了开发效率和用户交互体验。此外,其数据可视化组件有效支持了复杂物流数据的呈现和分析。然而,其在性能优化和定制化需求方面面临着挑战。最终,本文提出了一系列基于Ant Design Pro的物流系统开发最佳实践,并对其潜在的改进方向进行了讨论。研究结果为物流行业的信息系统开发提供了实用的指导,并为Ant Design Pro社区贡献了宝贵的实践经验。

Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence

The world produces vast quantities of high-dimensional multi-semantic data.However,extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging.Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features.The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection,because of its simplicity,efficiency,and similarity to reinforcement learning.Nevertheless,existing methods do not consider crucial correlation information,such as dynamic redundancy and label correlation.To tackle these concerns,the paper proposes a multi-label feature selection technique based on ant colony optimization algorithm(MFACO),focusing on dynamic redundancy and label correlation.Initially,the dynamic redundancy is assessed between the selected feature subset and potential features.Meanwhile,the ant colony optimization algorithm extracts label correlation from the label set,which is then combined into the heuristic factor as label weights.Experimental results demonstrate that our proposed strategies can effectively enhance the optimal search ability of ant colony,outperforming the other algorithms involved in the paper.

Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

Wireless Sensor Networks(WSNs)are a collection of sensor nodes distributed in space and connected through wireless communication.The sensor nodes gather and store data about the real world around them.However,the nodes that are dependent on batteries will ultimately suffer an energy loss with time,which affects the lifetime of the network.This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability.The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization(MFOA-EACO),where the Mayfly Optimization Algorithm(MFOA)is used to select the best cluster head(CH)from a set of nodes,and the Enhanced Ant Colony Optimization(EACO)technique is used to determine an optimal route between the cluster head and base station.The performance evaluation of our suggested hybrid approach is based on many parameters,including the number of active and dead nodes,node degree,distance,and energy usage.Our objective is to integrate MFOA-EACO to enhance energy efficiency and extend the network life of the WSN in the future.The proposed method outcomes proved to be better than traditional approaches such as Hybrid Squirrel-Flying Fox Optimization Algorithm(HSFLBOA),Hybrid Social Reindeer Optimization and Differential Evolution-Firefly Algorithm(HSRODE-FFA),Social Spider Distance Sensitive-Iterative Antlion Butterfly Cockroach Algorithm(SADSS-IABCA),and Energy Efficient Clustering Hierarchy Strategy-Improved Social Spider Algorithm Differential Evolution(EECHS-ISSADE).

A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

An Effective Optimization Algorithm for Ant Colony Vehicular Congestion Management

Adaptability and dynamicity are special properties of social insects derived from the decentralized behavior of the insects. Authors have come up with designs for software solution that can regulate traffic congestion in a network transportation environment. The effectiveness of various researches on traffic management has been verified through appropriate metrics. Most of the traffic management systems are centered on using sensors, visual monitoring and neural networks to check for available parking space with the aim of informing drivers beforehand to prevent traffic congestion. There has been limited research on solving ongoing traffic congestion in congestion prone areas like car park with any of the common methods mentioned. This study focus however is on a motor park, as a highly congested area when it comes to traffic. The car park has two entrance gate and three exit gates which is divided into three Isle of parking lot where cars can park. An ant colony optimization algorithm (ACO) was developed as an effective management system for controlling navigation and vehicular traffic congestion problems when cars exit a motor park. The ACO based on the nature and movement of the natural ants, simulates the movement of cars out of the car park through their nearest choice exit. A car park simulation was also used for the mathematical computation of the pheromone. The system was implemented using SIMD because of its dual parallelization ability. The result showed about 95% increase on the number of vehicles that left the motor park in one second. A clear indication that pheromones are large determinants of the shortest route to take as cars followed the closest exit to them. Future researchers may consider monitoring a centralized tally system for cars coming into the park through a censored gate being.

A Distributed Ant Colony Optimization Applied in Edge Detection

With the rise of image data and increased complexity of tasks in edge detection, conventional artificial intelligence techniques have been severely impacted. To be able to solve even greater problems of the future, learning algorithms must maintain high speed and accuracy through economical means. Traditional edge detection approaches cannot detect edges in images in a timely manner due to memory and computational time constraints. In this work, a novel parallelized ant colony optimization technique in a distributed framework provided by the Hadoop/Map-Reduce infrastructure is proposed to improve the edge detection capabilities. Moreover, a filtering technique is applied to reduce the noisy background of images to achieve significant improvement in the accuracy of edge detection. Close examinations of the implementation of the proposed algorithm are discussed and demonstrated through experiments. Results reveal high classification accuracy and significant improvements in speedup, scaleup and sizeup compared to the standard algorithms.

The Biology of <i>Szelenyiopria talitae</i>(Hymenoptera: Diapriidae): Larval Parasitoid of the Leaf-Cutting Ant <i>Acromyrmex subterraneus</i>(Hymenoptera: Formicidae)

The biology of a koinobiont parasitoid of leaf-cutting ant larvae, Szelenyiopria talitae (Hymenoptera: Diapriidae), was studied from naturally infested Acromyrmex subterraneus (Hymenoptera: Formicidae) nests. Nests were collected in the field from the Atlantic rainforest biome in the state of Rio de Janeiro. A total of fifty-three nests were collected from 2015 to 2018. Parasitized nests were only found during the months of September and October. Approximately 22% of the nests collected over a four-year period were found to have been parasitized by S. talitae. The mean within-nest parasitism rate was 66.3%. This diapriid displayed both solitary (14%) and gregarious parasitism (86%), with up to a maximum of 12 parasitoids developing within a single host. Gregarious parasitism with two (29%) or three (21%) S. talitae per host was most frequently observed. There was a positive correlation between the number of parasitoids per host and host size (dry weight), indicating that S. talitae females oviposited a higher number of eggs in larger hosts. There was also a negative correlation between S. talitae pharate adult size and the number of parasitoids per host, which could have been caused by sibling competition for limited host resources. The high levels of parasitism seen here had a debilitating effect on the colonies. Acromyrmex subterraneus is a serious pest in Brazil, and these studies lay the foundation for understanding the impact of S. talitae on ant populations.

主动网络工具集ANTS的主动包格式分析

目前国内发表的一些论文上关于ANTS的主动包格式介绍的不是很清楚、甚至是有些出入 ,而国外的有关文献中也没有相关内容的详细介绍。本文介绍了通过在搭建的ANTS主动网络平台上运行主动Ping命令 ,而后捕获该主动Ping数据包进行分析的方法 ,得出了ANTS的主动包 (封装体 )详细格式。

基于ANTS的主动路由支撑框架的设计与实现

在主动网工具包ANTS的基础上实现了一个QCAR原型系统,通过拓展ANTS的框架结构使其支持主动路由服务和沿途的QoS保障,并在该框架的基础上给出了一个主动路由的应用TraceRtApplication,通过具体的主动路由示例程序的实施,说明了如何在QCAR系统上开发新的应用。该文的研究和实现证明,与传统网络相比,在主动网基础上通过向网络中注入用户定制的、面向应用的路由需求代码,可以方便地实现主动路由定制和QoS保障。

主动网络执行环境ANTS的扩展设计及应用研究

由于国内在主动网络操作系统和执行环境方面的研究的薄弱,主动网络的应用研究受到了一定影响。基于该现状的考虑,分析了ANTS主动网络执行环境的优势与不足,针对其不足设计开发了一种构建灵活、能满足多种移动代码加载机制的执行环境EANTS,最后利用该平台进行了主动网络的管理应用研究,并实现了主动网络管理原型系统,研究成果为进一步进行主动网络应用研究提供了一种可选择的平台。

基于AntStream用户聚类的协同过滤推荐系统

系统规模的逐步扩大和用户兴趣的发展变化给传统协同过滤推荐系统带来了实时性减弱和准确性降低的问题。基于K-Means用户聚类的协同过滤技术虽然能在一定程度上解决这两个问题,算法本身却带有局部最优的缺陷。在保证实时性的前提下,为克服K-Means算法的缺陷,提出使用AntClass蚁群算法对用户聚类。同时提出将用户评分看作数据流,利用金字塔时间框架预处理数据,从而体现用户兴趣随时间的变化。于是,将AntClass蚁群算法和利用金字塔时间框架预处理过的数据流相结合,最终形成文中的AntStream算法。实验表明,AntStream算法不仅改善了传统协同过滤推荐系统的实时性问题,而且更大程度提高了推荐质量。

鲤鱼(Cyprinuscarpio,Cyprinidae)ants基因及其对鳞片发育的影响

ants(adenine nucleotide translocators),又称为ATP/ADP载体,利用Genefishing差异筛选技术对普通鲤鱼和德国镜鲤的皮肤转录产物进行筛选,得到了其中一个ant基因的部分片段,利用RT-PCR技术对皮肤中的ants基因进行钓取,得到6种不同的CDS序列。利用CLUSTALW对这6条翻译后的序列进行比对,发现这6条序列编码4种不同的氨基酸序列,表明ants基因至少有6种不同的转录产物(isoforms),但是在蛋白质水平上可能存在4种不同的翻译产物。利用NCBI上的blast对氨基酸序列进行同源性检索发现这4个蛋白产物与斑马鱼ant2最为相似,其相似度分别达到97%,97%,96%,98%。对处于不同分类地位的物种的ants基因与鲤鱼的4个ants表达产物进行进化树分析发现,这4个蛋白产物在93/100再现性水平上明显聚类为ant2,说明皮肤中表达的这些ants基因很可能是ant2。原位杂交结果显示,ant2在受精后4.5 h和6 h不表达,从受精后10 h开始在外包处强烈特异表达,在受精后12 h的胚胎中很弱表达,在受精后24 h的体节中特异强烈表达,在受精后48 h胚胎无表达,但是在着生鳞片的部位特异强烈表达,而在皮肤的其他部位则表达较弱或者不表达。以上的结果表明,ant2基因可能是通过不同的转录产物在精细调控鳞片的发育。

一种针对频率分配问题的改进ANTS算法

频率分配问题是近年来通信领域研究的热点。针对FAP问题提出了一种结合模拟退火算法的改进ANTS算法。运用模拟退火算法产生次优解,利用次优解分配初始信息素,并利用ANTS算法来寻求最佳方案。在ANTS算法的每个蚂蚁寻找局部最优过程中,为了加快运算速度,对局部寻优过程进行了改进。实验结果表明,在解质量相当的情况下,该算法能够大大地加快收敛速度,特别是针对一些较复杂的分配情况,效果明显。

Finding the Minimum Ratio Traveling Salesman Tour by Artificial Ants

Ants of artificial colony are able to generate good solutions to the famous traveling salesman problem (TSP). We propose an artificial ants algorithm for solving the minimum ratio TSP, which is more general than the standard TSP in combinatorial optimization area. In the minimum ratio TSP, another criterion concerning each edge is added, that is, the traveling salesman can have a benefit if he travels from one city to another. The objective is to minimize the ratio between total costs or distances and total benefits. The idea of this type of optimization is in some sense quite similar to that of traditional cost-benefit analysis in management science. Computational results substantiate the solution quality and efficiency of the algorithm.